# Splunk Senior Staff Software Engineer - Performance Optimization & Innovation (PerfOpt) at Cisco

AI Level 2, AI centrality 45 out of 100. Krakow, Poland.

## Details

- Company: [Cisco](https://jobsbylevel.com/companies/cisco)
- AI level: AI Level 2 (score 45 out of 100)
- Location: Krakow, Poland
- Posted: October 6, 2026
- Apply: https://jobsbylevel.com/go/3f4b2cf0-4965-487f-b3c4-03e9849e9c22

## Description

Meet The Team The Performance Optimization and Innovation (PerfOpt) team improves the Splunk customer experience through deep performance work, and sets Splunk's long-term performance standards through guidelines and design. We work where performance is won or lost: search and indexing hot paths, cache and bloomfilter efficiency, S3 transfer throughput, I/O workload management, and parallelism in the data retrieval path. It's a C++ core moving petabyte-scale data across a large distributed architecture, and the results land in what customers feel - search latency, ingest throughput, and infrastructure cost. We are also the organization's performance center of gravity: the benchmarking, design patterns, and engineering standards other teams adopt come from here. Your Impact Serve as the performance authority for critical issues, roadmap planning, architecture reviews, and customer conversations. Set technical direction across teams. Lead a performance domain end to end -hypothesis, instrumentation, design, measured customer-visible gain in production including cross-team problems nobody has framed yet. Architect for scale - design and re-architect subsystems in a distributed, petabyte-scale system: memory hierarchy, concurrency, I/O, tail-latency. Be responsible for the performance methodology - profiling and flame graph practice, lock contention analysis, benchmarking, CI regression gating. Introduce observability - design new telemetry sources and bring eBPF and continuous profiling into production use, so performance is measurable in the field, not just the lab. Enable leadership decisions - explain Directors and Managers on what the problem costs, what each option buys and costs, and the risk of inaction, with a recommendation you stand behind. A multi-week investigation becomes a one-page comparison they can act on in ten minutes. Deliver fast and make everyone faster - work agentically, and build reusable AI agentic workflows and tooling that cut the team's analysis loops from days to hours. Navigate AI optimization: point agents at changes that move the numbers, catch work that fails under a profile, redirect quickly. Lead and mentor senior and staff engineers. Minimum Qualifications Technical depth Expert-level C++ in production systems - memory management and allocators, move semantics, cache-friendly data structures, and a real command of the language's cost model. Deep performance engineering - depth across all of the below, production experience with several: CPU/memory profiling and flame-graph analysis (perf, eBPF, VTune), including off-CPU and continuous profiling. Lock contention resolution - hot mutexes, false sharing, atomics and memory ordering, lock-free techniques and when not to use them. Latency optimization in distributed architectures - tail latency, queuing, fan-out amplification, back-pressure, critical path analysis. Benchmarking - micro and workload benchmarks, sound test design and statistical analysis, sub-system validation CI regression detection. Performance modelling - analytical and capacity models that predict scaling limits and validate measured results Architecture and system design -design and re-architect existing solutions for performance, scalability and operability, and defend those designs to a critical audience. Docker and Kubernetes - performance characterization in containerized environments. Strong Python for tooling, benchmark harnesses, telemetry pipelines, and performance data analysis. Linux performance internals - scheduler, memory subsystem, page cache, filesystems, block I/O, network stack. Git and CI (e.g. GitLab CI) for automating builds, tests, benchmarks, and releases. Leadership Track record of informing leadership decisions - quantifying trade-offs, surfacing risk early. Distilling complex problems into comparable data points without losing the nuance or hiding uncertainty. Clear, concise, high-signal communication across audiences - mechanism-level with engineers,

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Source: https://jobsbylevel.com/jobs/splunk-senior-staff-software-engineer-performance-optimization-innovation-perfopt-at-cisco-43bd2b

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